U h @svdZddlmZddlmZmZmZddlmZddl m Z ddl m Z m Z ddlmZddlmZGd d d Zd S) !Experiment with different models.) annotations)ListOptionalSequence)BaseLLMPromptTemplate)get_color_mapping print_text)ChainLLMChainc@sJeZdZdZddddddZeddd dd d d Zd ddddZdS)ModelLaboratoryrNzSequence[Chain]zOptional[List[str]])chainsnamescCs|D]R}t|tstdt|jdkr8td|jt|jdkrtd|jq|dk rxt|t|krxtd||_ddtt|jD}t||_ ||_ dS) zyInitialize with chains to experiment with. Args: chains: list of chains to experiment with. zModelLaboratory should now be initialized with Chains. If you want to initialize with LLMs, use the `from_llms` method instead (`ModelLaboratory.from_llms(...)`)z;Currently only support chains with one input variable, got z/tmp/pip-unpacked-wheel-bo69hh5q/langchain/model_laboratory.py -sz,ModelLaboratory.__init__..) isinstancer ValueErrorlenZ input_keysZ output_keysrranger chain_colorsr)selfrrchainZ chain_rangerrr__init__s(    zModelLaboratory.__init__z List[BaseLLM]zOptional[PromptTemplate])llmspromptreturncsBdkrtdgddfdd|D}dd|D}|||dS) a)Initialize with LLMs to experiment with and optional prompt. Args: llms: list of LLMs to experiment with prompt: Optional prompt to use to prompt the LLMs. Defaults to None. If a prompt was provided, it should only have one input variable. N_inputz{_input})Zinput_variablestemplatecsg|]}t|dqS))llmr#r rr'r#rrr>sz-ModelLaboratory.from_llms..cSsg|] }t|qSrrr(rrrr?s)rr)clsr"r#rrrr)r from_llms1s zModelLaboratory.from_llmsrNone)textr$cCsttd|dt|jD]T\}}|jdk r8|j|}nt|}t|dd||}t||jt|ddqdS)a3Compare model outputs on an input text. If a prompt was provided with starting the laboratory, then this text will be fed into the prompt. If no prompt was provided, then the input text is the entire prompt. Args: text: input text to run all models on. zInput:  N)endz )colorr/)print enumeraterrrr runr)rr-rr nameoutputrrrcompareBs     zModelLaboratory.compare)N)N)__name__ __module__ __qualname____doc__r! classmethodr+r6rrrrrs rN)r: __future__rtypingrrrZ#langchain_core.language_models.llmsrZlangchain_core.prompts.promptr Zlangchain_core.utils.inputr r Zlangchain.chains.baser Zlangchain.chains.llmrrrrrrs